LDACS Design

Receiver Design for LDACS

The design of the receiver is a crucial part of LDACS. Basically, the receiver design is up to the implementer. Therefore, it is not defined in the specification. However, if LDACS is deployed using an inlay approach, severe interference, mainly from DME, may occur. If no countermeasures are taken, such interference considerably degrades LDACS transmission performance. In view of this situation, an adapted receiver design is essential.

Figure Dme Freq Domain 

We developed an adapted receiver design which is able to cope with severe impulsive interference. This concept is presented in the following.

LDACS uses OFDM as modulation technique. A typical OFDM receiver structure is shown in the following figure.

Figure Ofdm Receiver

Based on the received signal, the time and frequency offset of the signal is estimated and compensated. Next, the signal is transformed into the frequency domain by means of an FFT. The transmission channel is estimated based on inserted pilot symbols. The estimated transmission channel is used to equalize the signal. Finally, the signal is demodulated and decoded to obtain estimates of the transmitted information bits. Such a structure is well known, however, prone to strong interference. This issue can be relieved by introducing appropriate interference mitigation methods as presented in the following.

To account for various interference conditions, we propose interference mitigation including time domain and frequency domain components. In addition, an iterative reception is advised. Such a structure is shown in the following figure.

Figure Ofdm Receiver Int

The conventional LDACS receiver is extended by the blanking nonlinearity, the frequency-selective blanking nonlinearity, the RNN equalization, and the iterative loop. These blocks are explained in the following.

  • The blanking nonlinearity blanks, i.e., sets to zero all samples of the received signal with a magnitude exceeding a predefined threshold. In such a way, impulsive interference is suppressed reliably. However, the signal blanking affects the LDACS signal which is a significant drawback of this scheme. What makes the blanking nonlinearity appealing is its efficiency: compared to other algorithms, the blanking nonlinearity combines a low computational complexity with a reliable mitigation of the impulsive interference, leading to a moderate to high performance gain. In addition, the blanking nonlinearity is a non-parametric approach which means that it requires no particular knowledge regarding the statistics of the interference signals.
  • A critical issue of the blanking nonlinearity is that the entire LDACS signal is discarded during the blanking interval despite only a fraction of the LDACS spectrum might be affected by interference. To relieve this issue, we introduce the frequency-selective blanking nonlinearity. It profits from combining the received signal with the signal after the blanking nonlinearity. The approach is realized by first detecting the interference at each sub-carrier using a Neyman-Pearson-like testing procedure. Provided that interference has been detected, both the received and the blanked signal are subsequently optimally combined so as to maximize the signal quality for each sub-carrier. In this way, the blanking of the LDACS signal is restricted to sub-carriers that are affected by impulsive interference.
  • The blanking nonlinearity induces interference between the individual sub-carriers. This inter-carrier interference limits the performance of the blanking nonlinearity. An appropriate equalization, aiming to estimate and subtract the inter-carrier interference can mitigate the detrimental influence of inter-carrier interference significantly. We propose to adopt a recursive neural network (RNN) equalization to estimate and subtract the inter-carrier interference. The RNN equalization principle is based on estimating the inter-carrier interference by means of a non-linear decision function applied to the received data. Besides the received data, also a priori information can be incorporated into the estimation process.
  • A further performance gain can be achieved in an iterative loop. The a priori information obtained after decoding can be fed back to various receiver blocks for improving their performance. In addition, estimates of the transmission channel can further improve the performance of various receiver blocks.

By applying the presented interference mitigation algorithms and the adapted receiver structure, the LDACS transmission becomes robust against interference occurring in the aeronautical domain in the L-band, guaranteeing a reliable LDACS transmission.

LDACS Protocols

The data-link layer provides the necessary protocols to facilitate concurrent and reliable data transfer for multiple users. The functional blocks of the LDACS data link layer architecture are organized in two sub-layers: The medium access sub-layer and the logical link control sub-layer. The logical link control sub-layer manages the radio link and offers a bearer service with different classes of service to the higher layers. It comprises the Data Link Services (DLS), and the Voice Interface (VI). The medium access sub-layer contains only the Medium Access (MAC) entity. Cross-layer management is provided by the LDACS Management Entity (LME). The Sub-Network Protocol (SNP) provides the interface to the higher layers.


The MAC entity of the medium access sub-layer manages the access to the resources of the physical layer. Prior to fully utilizing the system, an aircraft has to register at the controlling ground-station in order to get a statically assigned dedicated control channel for the exchange of control data with the ground-station. The ground-station dynamically allocates the resources for user data channels according to the current demand as signaled by the aircraft. Except for the initial cell-entry procedure all communication between the aircraft and the controlling ground-station (including procedures for requesting and allocating resources for user data transmission and retransmission timer management), is fully deterministic and managed by the ground-station. Under constant load, the system performance depends only on the number of aircraft serviced by the particular ground-station and linearly decreases with increasing number of aircraft.

The DLS provides the acknowledged and unacknowledged exchange of user data. The ground-station LME provides centralized resource management for LDACS. It assigns transmission resources, provides mobility management and link maintenance. It assigns resources taking channel occupancy limitations (e.g. limiting the aircraft duty cycle to minimize co-site interference) into account. In addition, the LME provides dynamic link maintenance services (power, frequency and time adjustments) and supports adaptive coding and modulation. The VI provides support for virtual voice circuits. The voice interface provides only the transmission and reception services, while LME performs creation and selection of voice circuits. Voice circuits may either be set-up permanently by the ground-station LME to emulate party-line voice or may be created on demand.

LDACS shall become a sub-network of the Aeronautical Telecommunications Network (ATN). The SNP provides the LDACS interface to the network layer and a network layer adaptation service required for transparent transfer of Network layer Protocol Data Units (N-PDUs) of possibly different network protocols (ATN/IPS and ATN/OSI). The SNP also provides compression and cryptographic services required for improving and securing the wireless channel.

A detailed specification of the LDACS protocols can be found here.

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